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310 results for “Tree growth”
Data from: Models of knot and stem development in black spruce trees indicate a shift in allocation priority to branches when growth is limited
The branch autonomy principle, which states that the growth of individual branches can be predicted from their morphology and position in the forest canopy irrespective of the characteristics of the tree, has been used to simplify models of branch growth in trees. However, observed changes in allocation priority within trees towards branches growing in light-favoured conditions, referred to as 'Milton's Law of resource availability and allocation,' have raised questions about the applicability of the branch autonomy principle. We present models linking knot ontogeny to the secondary growth of the main stem in black spruce (Picea mariana (Mill.) B.S.P.), which were used to assess the patterns of assimilate allocation over time, both within and between trees. Data describing the annual radial growth of 445 stem rings and the three-dimensional shape of 5,377 knots were extracted from optical scans and X-ray computed tomography images taken along the stems of 10 trees. Total knot to stem area increment ratios (KSR) were calculated for each year of growth, and statistical models were developed to describe the annual development of knot diameter and curvature as a function of stem radial increment, total tree height, stem diameter, and the position of knots along an annual growth unit. KSR varied as a function of tree age and of the height to diameter ratio of the stem, a variable indicative of the competitive status of the tree. Simulations of the development of an individual knot showed that an increase in the stem radial growth rate was associated with an increase in the initial growth of the knot, but also with a shorter lifespan. Our results provide support for 'Milton's Law,' since they indicate that allocation priority is given to locations where the potential return is the highest. The developed models provided realistic simulations of knot morphology within trees, which could be integrated into a functional-structural model of tree growth and above-ground resource partitioning.
Climate anomalies and neighbourhood crowding interact in shaping tree growth in old-growth and selectively-logged tropical forests
<p>Species mean information for the six leaf water-related traits used in the paper titled: Climate anomalies and neighbourhood crowding interact in shaping tree growth in old-growth and selectively-logged tropical forests.</p>
Soil variation response is mediated by growth trajectories rather than functional traits in a widespread pioneer Neotropical tree
<p>Description of Soil_DataTrees.csv</p> <ul> <li>Tree_label: Label of trees on the field, there are 70 trees</li> <li>Tree_site: Site on which the tree has been sampled; COU: Counami; SPA: Sparouine</li> <li>Descr_date: Date of tree sampling</li> <li>Soil_type: Type of soil; FS: ferralitic soils; WS: white-sand soils</li> <li>Soil_sample: Label of soil sample</li> <li>H2Osoil: Soil water content (g kg<sup>-1</sup>)</li> <li>Clay: Soil clay content (g kg<sup>-1</sup>)</li> <li>SiltTh: Soil thin silt content (g kg<sup>-1</sup>)</li> <li>SiltCo: Soil coarse silt content (g kg<sup>-1</sup>)</li> <li>SandTh: Soil thin sand content (g kg<sup>-1</sup>)</li> <li>SandCo: Soil coarse sand content (g kg<sup>-1</sup>)</li> <li>Csoil: Soil carbon content (g kg<sup>-1</sup>)</li> <li>Nsoil: Soil nitrogen content (g kg<sup>-1</sup>)</li> <li>CNsoil: Soil carbon:nitrogen ratio</li> <li>MOsoil: Soil organic matter content (g kg<sup>-1</sup>)</li> <li>Ptotsoil: Soil total phosphorus content (g 100g<sup>-1</sup>)</li> <li>Kcec: Soil potassium:CEC[cation-exchange capacity] ratio</li> <li>Cacec: Soil calcium:CEC ratio</li> <li>Mgcec: Soil magnesium:CEC ratio</li> <li>Nacec: Soil sodium:CEC ratio</li> <li>Alcec: Soil aluminum:CEC ratio</li> <li>Fecec: Soil iron:CEC ratio</li> <li>Mncec: Soil manganese:CEC ratio</li> <li>Hcec: Soil hydrogen:CEC ratio</li> <li>pHsoil: Soil pH (cmol kg<sup>-1</sup>)</li> <li>CECsoil: Soil cation-exchange capacity (cmol kg<sup>-1</sup>)</li> <li>Indexsoil: Soil index of fertility = (K+Ca+Mg+Na)/CEC</li> </ul> <p>K, Ca, Mg, Na, Al, Fe, Mn, H were initially measured in cmol kg<sup>-1</sup></p> <p> </p> <p>Description of Trait_DataTrees.csv</p> <ul> <li>Tree_label: Label of the tree on the field. There are 70 trees</li> <li>Tree_site: Site of sampling; COU: Counami; SPA: Sparouine</li> <li>Descr_date: Date of tree sampling</li> <li>Calendar_day: Day of the year (between 1 and 365) of tree sampling</li> <li>Soil_type: Type of the soil; FS: ferralitic soils; WS: white-sand soils</li> <li>PCA1_soil: Coordinates of the trees along the first axis of PCA (principal component analysis) with soil data, used as a quantitative soil index on FS-WS soil gradient</li> <li>mesHeight: Measured tree height (m)</li> <li>Height: Tree height based on the sum of all internodes length (m)</li> <li>Dbh: Tree diameter at height breast (cm)</li> <li>Age: Tree age (year)</li> <li>Order: Number of branching order</li> <li>Brtot: Total number of branches branching from the trunk</li> <li>Leaftot: Total number of leaves</li> <li>Fltot: Total number of inflorescences</li> <li>Acrown: Total estimated crown area (m²)</li> <li>INA1: Number of trunk internodes</li> <li>Brbear: Number of A2 bearing branches</li> <li>Brdead: Number of A2 dead branches</li> <li>Br1stH: First branching height</li> <li>Fl1stH: First flowering height</li> <li>Br1stIN: First branching node rank</li> <li>Fl1stIN: First flowering node rank</li> <li>Br1stAge: First branching age</li> <li>Fl1stAge: First flowering age</li> <li>LL: Leaf lifespan (day)</li> <li>Lpet: Petiole length (cm)</li> <li>Apet: Petiole cross-sectional area (mm²)</li> <li>Nlobe: Number of leaf lobes</li> <li>LMA: Leaf mass area (g m<sup>-2</sup>)</li> <li>Thleaf: Leaf thickness (µm)</li> <li>Aleaf: Estimated individual leaf area (cm²)</li> <li>Chlleaf: Leaf chlorophyll content (mg ml<sup>-1</sup>)</li> <li>H20resleaf: Leaf residual water content (%)</li> <li>dC13leaf: δ<sup>13</sup>C content (‰)</li> <li>Cleaf: Leaf carbon content (g kg<sup>-1</sup>)</li> <li>Nleaf: Leaf nitrogen content (g kg<sup>-1</sup>)</li> <li>CNleaf: Leaf carbon:nitrogen ratio</li> <li>Pleaf: Leaf phosphorus content (g kg<sup>-1</sup>)</li> <li>Kleaf: Leaf potassium content (g kg<sup>-1</sup>)</li> <li>WSG: Wood specific gravity (g cm<sup>-3</sup>)</li> </ul> <p> </p> <p> </p> <ul> <li>Tree_label: Label of the tree</li> <li>Soil_type: Type of the soil; FS: ferralitic soils; WS: white-sand soils</li> <li>rank_base: Rank of the internode from the base of the tree</li> <li>rank_top: Rank of the internode from the apex of the tree</li> <li>phyllochron: Phyllochron, number of days for the production of one leaf</li> <li>date: Estimated date of tree germination</li> <li>nb_day_base: Number of days since estimated germination</li> <li>nb_day_top: Age of the internode in days at tree sampling</li> <li>AS_rank_base: Rank of the annual shoot from the base of the tree</li> <li>As_rank_top: Rank of the annual shoot from the apex of the tree</li> <li>AS_nodes_base: Number of internodes per annual shoot</li> <li>AS_length_base: Length of the annual shoot (cm)</li> <li>AS_br_base: Number of A2 branches on the annual shoot</li> <li>AS_flo_base: Number of inflorescences on the annual shoot</li> <li>lg_en: Internode length (cm)</li> <li>ht_en: Cumulated height of the tree based on the sum of internode length (cm)</li> <li>ma_lgen: Moving average of internode length</li> <li>resi_lgen: Residuals of internode length</li> </ul> <p> </p>
Data from: A multi-decade experiment shows that fertilization by salmon carcasses enhanced tree growth in the riparian zone
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Data from: Greater growth stability of trees in marginal habitats suggests a patchy pattern of population loss and retention in response to increased drought at the rear edge
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Data from: Models of knot and stem development in black spruce trees indicate a shift in allocation priority to branches when growth is limited
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Fig. 1 in The comparative growth rates of indigenous street and garden trees in Grahamstown, South Africa
Fig. 1. Mean annual diameter increment (cm/yr) of indigenous street (n = 45) and garden (n = 56) trees relative to their age (Species abbreviations are genus and species (4 and 3 letters, respectively; the species 'other' refers to nine species for which the sample was less than three stems per species).
The Populus Homeobox Gene ARBORKNOX2 Regulates Secondary Growth in trees
GEO Series GSE15595. Populus sp.; Populus. 10 samples. Type: Expression profiling by array.
Macroscopic Models of Clique Tree Growth for Bayesian Networks
In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to characterizing clique tree growth as a function of increasing Bayesian network connectedness, specifically: (i) the expected number of moral edges in their moral graphs or (ii) the ratio of the number of non-root nodes to the number of root nodes. In experiments, we systematically increase the connectivity of bipartite Bayesian networks, and find that clique tree size growth is well-approximated by Gompertz growth curves. This research improves the understanding of the scaling behavior of clique tree clustering, provides a foundation for benchmarking and developing improved BN inference algorithms, and presents an aid for analytical trade-off studies of tree clustering using growth curves. **Reference:** O. J. Mengshoel, "Macroscopic Models of Clique Tree Growth for Bayesian Networks." In Proc. of the 22nd National Conference on Artificial Intelligence (AAAI-07). July 2007, Vancouver, Canada, pp. 1256-1262. **BibTex Reference:** @inproceedings{mengshoel07macroscopic, author = "Mengshoel, O. J.", title = "Macroscopic Models of Clique Tree Growth for {Bayesian} Networks", year = "2007", booktitle = {Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI-07)}, pages = "1256-1262", address = "Vancouver, British Columbia" }
Data used in the paper: Topography imposes an abiotic filter on tree growth in a restored area
<p>This repository contains original values of relative growth rates, leaf traits, UTM coordinates, and topography features used in the article " Topography imposes an abiotic filter on tree growth in a restored area ". <em>Theoretical and Experimental Plant Physiology</em></p> <p>Description of files:</p> <p>(1) "Data_five_individuals.csv": Original values of relative growth rates, leaf traits, and topography features measured for each species in each slope aspect (north and south) in the studied hill. Relative Growth Rates: H.RGR, height; SLD.RGR, soil-level diameter; CS.RGR, canopy size. Leaf traits: SLA, specific leaf area; Car, total carotenoids; Chlab, total chlorophyll; Chlab<em>.</em>Car, total chlorophyll/total carotenoids; Fv.Fm, the maximum quantum yield of PSII; Fv.F0, variable fluorescence to minimum fluorescence; qP, photochemical quenching; NPQ, non-photochemical quenching.</p> <p>(2) "Data_ten_individuals.csv": Original values of relative growth rates, UTM coordinates, and topography features measured for each species in each slope aspect (north and south) in the studied hill. Relative Growth Rates: H.RGR, height; SLD.RGR, soil-level diameter; CS.RGR, canopy size.</p>
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